The new world of RNA diagnostics and therapeutics

Abstract

The 5th Workshop IRE on Translational Oncology was held in Rome (Italy) on 27-28 March at the IRCCS Regina Elena National Cancer Institute. This meeting entitled "The New World of RNA diagnostics and therapeutics" highlightes the significant progress in the RNA field made over the last years. Research moved from pure discovery towards the development of diagnostic biomarkers or RNA-base targeted therapies seeking validation in several clinical trials. Non-coding RNAs in particular have been the focus of this workshop due to their unique properties that make them attractive tools for the diagnosis and therapy of cancer.This report collected the presentations of many scientists from different institutions that discussed recent oncology research providing an excellent overview and representative examples for each possible application of RNA as biomarker, for therapy or to increase the number of patients that can benefit from precision oncology treatment.In particular, the meeting specifically emphasized two key features of RNA applications: RNA diagnostic (Blandino, Palcau, Sestito, Díaz Méndez, Cappelletto, Pulito, Monteonofrio, Calin, Sozzi, Cheong) and RNA therapeutics (Dinami, Marcia, Anastasiadou, Ryan, Fattore, Regazzo, Loria, Aharonov).

Keywords: Cell cycle regulation; Epigenetics; RNA evolution; RNA structure; Splicing.

Fig. 1

Molecular dissection of breast cancer metastases. We collected breast cancer metastases from different sites, and we performed multiomic analyses, including whole exome sequencing (WES), bulk RNA sequencing (RNAseq), and miRNA profiling. The integrated analyses allowed to the identification of altered pathways in breast cancer metastases and novel therapeutic approaches that will be evaluated on patients-derived organoids

Fig. 2

Targeting TRF2 by LNPs-miR-182-3p in triple-negative breast cancer. A Targeting of 3'UTR-TRF2 by selected miRNAs was tested by high-throughput luciferase screening. B Western blot of TRF2 expression in tumor cells transfected with miR-182-3p or miR-Control is shown. C Representative images show the telomeric and pericentromeric DNA damage induced by miR-182-3p in MDA-MB-231 cells. D Cell confluence or apoptosis activation in MDA-MB-436 cells, transfected with the indicated miRNAs, were monitored by live-cell imaging (Incucyte) or analysed by flow cytometry (FACS), respectively. E Scheduling of treatment (top/right panel); Analysis of tumor inhibition after treatment with LNPs-miR-182-3p or its relative controls (bottom/right panel); TRF2 and γH2AX expression in tumor tissues was analyzed by immunohistochemistry (IHC) (middle panel); Representative images show mice with artificial brain tumor generated by intracranial injection of MDA-MB-231. Mice were treated with LNPs-miR-182-3p or its control (left panel)

Fig. 3

Mechanistic hypothesis for the p53-stimulatory role of MEG3. Folding of the MEG3 core exposes regulatory motifs to p53 activators/repressors to recruit p53 on chromatin, and fine-tune the expression of p53 target genes

Fig. 4

miRNA-aided therapy. Delivery of miR-34a mimics or miR-24 inhibitors miRNAs in B-cell lymphoma to fine-tune co-inhibitory and co-stimulatory signals, to facilitate immune escape (Biorender)

Fig. 5

CircPVT1 exerts an oncogenic activity by acting as a miRNAs sponge regulating the expression of pivotal metabolic genes

Fig. 6

The figure represents the multifaceted role of miR-579-3p in BRAF-mutant metastatic melanoma. A The circulating levels of miR-579-3p can be easily determined in liquid biopsies and are able to predict response to targeted therapy in patients. B Lipid nanoparticles (LNPs) delivering miR-579-3p can prolong the efficacy of targeted therapies in melanoma xenograft models

Fig. 7

Genome-wide approaches to study miRNA involved in DLBCL response to treatment. (A) Small-RNA sequencing on serum samples from DLBCL patients responding or refractory to R-CHOP treatment to identify miRNAs as predictive biomarkers. (B) CRISPR/Cas-9 library screening on a cell model of drug resistance to identity miRNAs as potential therapeutic targets (image created with BioRender.com)

Fig. 8

A schematic diagram illustrating the ability of ET-1-driven ET_AR/miR-200/ZEB1/GSDME circuitry to fuel metastasis progression and reprogram the tumour immune microenvironment (TIME) in HG-SOC cells

Fig. 9

Panel A PCA plot. Panel B Volcano plot for OS vs normal bone specimens

Fig. 10

Impact of the miR-1/-26a-1/-487b signature on the main biological functions in glioma. A The miRNA signature inhibits invadopodia activity by targeting invadopodia-related genes that encode for TKS4, TKS5 and EFHD2 proteins. B Schematic representation of the main three-miRNA signature impacted functions, including response to treatment

Fig. 11

Model of the axis Che-1/miR-590-3p/ TAZ that sustains the tumor progression in MM cells. In MM cells Che-1 is upregulated and recruited on the promoter of EIF4H, the host gene of miR-590-3p. The miRNA downregulates TAZ both on transcriptional and post-translational level promoting cell proliferation

Fig. 12

c-Myc-dependent transcription activation of a signature of mRNAs allows the acquisition of resistance to the alpelisib treatment, in patient-derived xenografts of head and neck squamous cell carcinoma

Fig. 13

A-B RT-qPCR of circHIPK2 and circHIPK3 in: A tumor tissue of CRC patients (Tum) and matched normal tissue (Norm); B plasma samples of healthy volunteers (Norm) and CRC patients (Tum)

Fig. 14

The biological activity of miRNAs involved in cancer and the therapeutic applications

Fig. 15

Cumulative lung cancer incidence by baseline vs yearly MSC repetition in participants with an LDCT-indeterminate/positive (LDCT +) finding. (n = 655)

Fig. 16

ENLIGHT-matched treatments are associated with better patient response: The Odds Ratio (OR, Y axis) for response of cases matched by ENLIGHT vs. cases unmatched by ENLIGHT for individual blinded cohorts, along with the OR for the aggregation of all cohorts. Drug and sample sizes are given on the X-axis labels. The red horizontal dashed line denotes an OR of 1, as expected by chance. Cohorts for which OR is significantly larger than 1 according to Fisher’s exact test are denoted with asterisks. a Based on bulk transcriptomics. b Based solely on H&E slides